The purpose of the study was to label Flixotide (fluticasone propionate [FP] with HFA propellant), with technetium-99m and validate that (99m)Tc acts as a suitable marker for FP when delivered via pMDI-spacer. Sodium pertechnetate was mixed with 5 mL of butanone. (99m)Tc was extracted into butanone and transferred into an empty canister. The (99m)Tc lined canister was heated, and the butanone evaporated to dryness. A supercooled commercial Flixotide canister was decrimped, and the contents transferred to the (99m)Tc lined canister and recrimped. The particle size distribution of FP and (99m)Tc from 10 radiolabeled canisters was measured using an Anderson cascade impactor calibrated to 28.3 L/min, and compared to commercial FP. The drug (FP) content of each particle size fraction was measured using ultraviolet spectrophotometry and the (99m)Tc level in each fraction was measured using an ionization chamber. The percentage of particles in the fine particle fraction (<;4.7 microm) and the percentage of (99m)Tc from commercial and radiolabeled canisters were compared. The mean (SD) % FP in the fine particle fraction, before and after label was 43.2 (1.8) % and 43.9 (2.6) %, respectively. The mean (SD) % (99m)Tc in the fine particle fraction was 42.1 (5.1) %. The mean %FP exiting spacer at (<4.7 microm) before labeling was not significantly different from the mean % FP exiting spacer at (<4.7 microm) after labeling (p > 0.05). The mean % (99m)Tc attached to particles at (<4.7 microm) after radiolabeling was not significantly different from the mean % FP levels (p > 0.05). The validation in this study indicates that (99m)Tc can act as a suitable marker for HFAFP, delivered via pMDI-spacer.
Teratogenicity poses severe threats to patient safety. Stem-cell-based in vitro systems are promising tools to predict human teratogenicity. However, current in vitro assays are limited because they either capture effects on a certain germ layer, or focus on a subset of predictive markers. Here we report the characterization and critical assessment of TeraTox, a newly developed multi-lineage differentiation assay using 3D human induced pluripotent stem cells. TeraTox probes stem-cell derived embryoid bodies with two endpoints, one quantifying cytotoxicity and the other inferring the teratogenicity potential with gene expression as a molecular phenotypic readout. To derive teratogenicity potentials from gene expression profiles, we applied both unsupervised machine-learning tools including factor analysis and supervised tools including classification and regression. To identify the best predictive model for the teratogenicity potential that is explainable, we systematically tested 64 machine-learning model architectures and identified the optimal model, which uses expression of 77 representative germ-layer genes, summarized by 10 latent germ-layer factors, as input for random-forest regression. We combined measured cytotoxicity and inferred teratogenicity potential to predict concentration-dependent teratogenicity profiles of 33 approved pharmaceuticals and 12 proprietary drug candidates with known in vivo data. Compared with the mouse embryonic stem cell test, which has been in routine use for more than a decade, the TeraTox assay shows higher sensitivity, particularly towards teratogens impairing ectodermal development or stem-cell renewal, and a more balanced prediction performance. We envision that further refinement and development of TeraTox has the potential to reduce and replace animal research in drug discovery and to improve preclinical assessment of teratogenicity.
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